AI skills is being rolled out progressively. If you don’t see the AI skills
section in your reports yet, reach out to us and we’ll enable it for your
organization.
Who can see it?
- The organization-wide AI skills report follows the same access as other organization reports: Team lead, Manager, and Admin roles.
- Team and individual AI skills views follow the team and individual report access rules — members can see their own AI skills, managers and admins can see anyone’s.
- AI skills is a paid feature. On free plans the page shows a preview behind a paywall.
Where to find it
The same AI skills breakdown appears at three scopes, each reachable from its report’s section navigation:
You can also get there from the Overview page: the AI skills radar in the health scores section links to the full report, and clicking a specific axis on that radar deep-links straight into that skill’s drilldown.
All views respect the standard filter bar (date range, teams, repositories) and the time granularity selector.
The ten skills
Each axis is normalized to 0–10. Hover any score box or radar axis label to see its description in the app.Measured from your code platform
These three axes come from PR data (GitHub, GitLab, or Bitbucket) combined with your AI tool cost data:Measured from AI conversations
These seven axes come from scored coding-agent conversations. Weave analyzes each session from the Weave plugin for Claude Code, Cursor, GitHub Copilot, or Codex and scores it 1–10 on every dimension; the report shows the average over the selected period.The overall AI skills score only appears once at least one conversation-based
skill has data. Without a Claude Code, Cursor, GitHub Copilot, or Codex plugin
connection, the page shows a connect-your-data empty state instead of scores
derived from zero conversations.
The overall score and score boxes
The headline Overall AI skills score (0–10) is a weighted average of the ten axes. By default all axes weigh equally; admins can retune the weights with the gear icon on the overall-score box (weights can be set organization-wide or per team). Below it, one score box per skill shows that axis’s current value. A box shows — when no data is flowing for that axis (for example, no cost data connected for output per dollar). Every box is clickable:- The seven conversation skills open the conversation drilldown focused on that skill.
- Percent AI output opens the AI output percentage PR-level drilldown.
- Output per dollar opens a drilldown of PRs with their code output and attributed AI cost.
- AI code turnover opens the code turnover drilldown.
- The overall score opens the drilldown across all scored conversations in the date range.
Charts
The main row shows three charts side by side:- AI output % — the adoption trend over time
- AI skills radar — all ten axes as a radar polygon, with comparison overlays
- AI skills — the overall composite score trend. Click any point to open the conversations scored in that period.
Radar comparison overlays
The radar draws dashed comparison lines that adapt to the scope you’re viewing:
The cross-org lines respect the dashboard Benchmarks display toggles (Median and Top 10%), the same ones that govern benchmark lines on other charts.
Below the chart row, the report also includes a per-skill trend chart for each conversation axis, so you can see how planning, verification, and the rest move over time.
AI skills insights
On individual and team views, an AI skills insights panel sits above the charts. It synthesizes the period’s AI sessions into a plain-English weekly summary plus actionable insight cards:- A week selector switches between weeks (most recent shown by default).
- The week’s session count is clickable and opens the conversation drilldown for that week.
- Each insight card shows a title, detail, and the skill it relates to. Cards tagged with a skill are clickable and open the by-skill drilldown scoped to that week, so you land directly in the sessions that drove the insight.
Conversation drilldown
Clicking a conversation skill, the overall score, a composite chart point, or an insight card opens the conversation drilldown — a table of individual scored AI sessions. Every row is one conversation, with:- Title — a short, auto-generated description of what the session was about
- Author and Source — who ran the session and in which tool (Claude Code, Cursor, or Codex)
- Activity — when the session took place
- Scores — when focused on one skill, that skill’s score plus Why this score and How to improve explanations; when opened from the overall score, the Overall score, all skill scores, the full Rationale, and the Strongest positive signal / Strongest negative signal
Exporting a conversation
Each drilldown row has a download button that exports the conversation as a JSON file containing all scores, the full rationale with per-dimension explanations, and the turn-by-turn transcript (user prompts, agent messages, and tool calls; very large tool inputs are summarized rather than included verbatim). Access is enforced server-side with the same rules as viewing that member’s data in the app.AI skills in the individual report table
On the individual report, the members table includes an expandable AI skills column showing each person’s overall score. Expanding the group adds one column per axis, so you can sort and compare any specific skill across engineers.How scoring works
1
Sessions are captured
The Weave plugin for Claude Code,
Cursor, GitHub Copilot, or Codex reports each coding session — prompts,
agent messages, and tool calls.
2
Conversations are scored
Weave’s scoring model analyzes each conversation and assigns a 1–10 score
per dimension, along with a written rationale, per-dimension explanations,
and improvement suggestions. New conversations are typically scored within
about an hour.
3
Scores roll up
Session scores average into the per-skill trends and radar for the selected
date range and scope, and combine with the PR-based axes into the weighted
overall score.
Prerequisites
For the conversation-based skills (most of the report)
For the conversation-based skills (most of the report)
Engineers need the Weave plugin
for Claude Code, Cursor, GitHub Copilot, or Codex installed and reporting.
These capture the per-session signals (prompts, agent messages, tool calls)
that conversation scoring requires — org-level telemetry alone is not enough.For Codex, agent messages come from the Weave hooks the install command
registers, and those hooks need a one-time trust approval on each machine
before they run. See hook trust prompt.
For percent AI output
For percent AI output
A connected code platform (GitHub,
GitLab, or
Bitbucket) plus AI tool
attribution data.
For output per dollar
For output per dollar
AI spend data — auto-detected tool subscriptions, entries under
Settings → Financial, or ingested cost telemetry. See AI tool
costs.
For AI code turnover
For AI code turnover
A connected code platform with enough merged PR history to compute code
turnover.
Improving your scores
- Plan before you delegate — scope the task, state constraints and success criteria up front (raises Planning and Task handling)
- Verify AI output — run the code, run the tests, review the diff instead of accepting on faith (raises Verification and Code quality)
- Stay engaged — question suspicious output and steer the agent rather than rubber-stamping (raises Ownership)
- Iterate constructively — give specific feedback when the AI misses, instead of restarting or fighting it (raises Collaboration)
- Parallelize where it fits — use subagents for independent workstreams on larger tasks (raises Agent parallelization)
- Read your own drilldowns — each scored conversation includes “Why this score” and “How to improve” written for that specific session
Public API
Available fromGET /metrics as ai_skills: the overall 0–10 composite score. Supports group_by=account and weekly granularity. This is not GET /skill-usage, which returns skill invocation counts.